Remote depth sensing via relayed depth from diffusion

ABSTRACT

Remote depth sensing techniques are described via relayed depth from diffusion. In one or more implementations, a remote depth sensing system is configured to sense depth as relayed from diffusion. The system includes an image capture system including an image sensor and an imaging lens configured to transmit light to the image sensor through an intermediate image plane that is disposed between the imaging lens and the image sensor, the intermediate plane having an optical diffuser disposed proximal thereto that is configured to diffuse the transmitted light. The system also includes a depth sensing module configured to receive one or more images from the image sensor and determine a distance to one or more objects in an object scene captured by the one or more images using a depth by diffusion technique that is based at least in part on an amount of blurring exhibited by respective said objects in the one or more images.

BACKGROUND

Depth sensing may be utilized by computing devices to support a varietyof different functionality. For example, conventional techniques such asof time-of-flight cameras, structured-light cameras, and so on may beused to determine a location of an object within an object scene intwo-dimensional space (i.e., “X” axis and “Y” axis) as well as a depthof the object from a camera that captures the image, i.e., a “Z” axis.This may be used to map an object space in three dimensions, detectgestures as part of a natural user interface (NUI), and so forth.

There are primarily two kinds of imaging techniques utilized forgenerating depth images—passive and active. Passive depth cameras arereliant on the amount of texture information present in the scene, andit is challenging to achieve reliable performance in diverseenvironments. Active depth cameras, on the other hand, havesignificantly higher reliability as these cameras estimate depthinformation by measuring response to a light source that is part of thesystem. Conventional time-of-flight techniques utilized to perform depthsensing, however, require high powered and high frequency illuminationand are susceptible to multipath degradation, as these techniques arebased on timing of reflected light back to a custom image sensor. Thecustomization of the sensor also adds significant cost to the device.Conventional structured-light cameras, on the other hand, requirecalibration against a diffraction optical element (DOE) and there arestringent requirements on maintaining this calibration through the lifeof the system for guaranteeing correct depth. This calibrationrequirement makes it hard to implement structured light depth systems inproducts that might undergo significant mechanical and thermaldistortions—such as mobile products. Additionally, the depth spatialresolution is dependent on the spacing of the dots in the DOE pattern,and there is often a tradeoff between resolution and being able toidentify each dot from a very dense pattern. Depth from defocus isanother technique that makes use of known lens properties to infer depthbased on the amount of defocus/blur rendered by scene points, as suchblur is dependent on depth and lens properties, such as depth of fieldin object space and depth of focus at sensor. This technique can beimplemented in both, active and passive flavors, with the active mode(say, with an illumination systems including a laser and DOE) having theadvantage that there will be no dependence on the amount of scenetexture, as it is added or overlaid onto the object scene using suchstructured light illuminator. The challenge for this technique has beenthat in order to achieve good depth accuracy, a large aperture lens isrequired which limits viability in mobile products, due to factorsincluding size and weight as well as cost.

SUMMARY

Remote depth sensing techniques are described via relayed depth fromdiffusion. In one or more implementations, a remote depth sensing systemis configured to sense depth as relayed from diffusion. The systemincludes an image capture system including an image sensor and animaging lens configured to transmit light to the image sensor through anintermediate image plane that is disposed between the imaging lens andthe image sensor. The intermediate plane has an optical diffuserdisposed proximal thereto that is configured to diffuse the transmittedlight. The system also includes a depth sensing module configured toreceive one or more images from the image sensor and determine adistance to one or more objects in an object scene captured by the oneor more images using a depth by diffusion technique that is based atleast in part on an amount of blurring exhibited by respective objectsin the one or more images.

In one or more implementations, a technique is described to performremote depth sensing of objects in an image scene using diffusion by acomputing device. The technique includes receiving one or more images bythe computing device of an image scene from an image capture systemhaving diffusion applied internally by the image capture system,determining a distance to one or more objects in the image scene by thecomputing device based on an amount of blurring exhibited by the one ormore objects in the received images, and outputting the determineddistance by the computing device.

In one or more implementations, an image capture system includes animaging lens configured to transmit light from an object scene into animage space including an intermediate image plane, an image sensorconfigured to capture the transmitted light from the image space to formone or more images of the intermediate image plane through use of animaging relay, and an optical diffuser disposed within an intermediateimage plane between the imaging lens and the image sensor, or furtherbetween the imaging lens and imaging relay, the optical diffuserenabling an increase in depth of focus available to the image sensorfrom the imaging relay, serving as an ‘ambient’ diffuser for the imagespace of the object scene, the image space being in proximity to theintermediate image plane.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is described with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different instances in thedescription and the figures may indicate similar or identical items.Entities represented in the figures may be indicative of one or moreentities and thus reference may be made interchangeably to single orplural forms of the entities in the discussion.

FIG. 1 is an illustration of an environment in an example implementationthat is operable to employ the relayed depth from diffusion techniquesdescribed herein.

FIG. 2 depicts a system in an example implementation showing an imagecapture system of FIG. 1 in greater detail as capturing an image of anobject scene.

FIG. 3 depicts an example implementation of a diffuser of FIG. 2 that isconfigured to mechanically switch between polarized and non-polarizedstates.

FIG. 4 depicts an example implementation of the optical diffuser of FIG.2 that is configured to electrically switch between polarized andnon-polarized states.

FIG. 5 depicts a system in an example implementation of apolarization-sensitive microlens array and polarization-sensitivediffuser.

FIG. 6a depicts a system in an example implementation showing a firstpolarization switching option.

FIG. 6b depicts a system in an example implementation showing a secondpolarization state based option that supports simultaneous capture of aplurality of polarization states.

FIGS. 7 and 8 depict graphs illustrating examples of nonlinear mappingto a z distance deduced by the depth from diffusion techniques whichfollows optical image conjugates of the image capture system of FIG. 2.

FIG. 9 depicts an example graph of spotsize blur for various objectdistances for a diffuser placed at image space conjugate for far objectdistance.

FIG. 10 depicts an example graph of spotsize blur for various objectdistances for a diffuser placed at image space conjugate for near objectdistance.

FIG. 11 depicts an example implementation of time-sequential depth fromdiffusion using a polarization-sensitive microlens array.

FIG. 12 is a flow diagram depicting a procedure in an exampleimplementation in which a technique is described to perform remote depthsensing of objects in an image scene using diffusion by a computingdevice.

FIG. 13 illustrates an example system including various components of anexample device that can be implemented as any type of computing deviceas described with reference to FIGS. 1-9 to implement embodiments of thetechniques described herein.

DETAILED DESCRIPTION

Overview

Techniques used to determine depth from diffusion typically haveincreased accuracy over other conventional techniques such as depth fromdefocus. Conventional techniques that are utilized to perform depth fromdiffusion, however, require use of optical diffusers within an objectspace being examined, and is thus impractical for normal usagescenarios.

Remote depth sensing techniques are described via relayed depth fromdiffusion. In one or more implementations, an image capture systemincludes an image sensor used to capture images and an imaging lensconfigured to transmit light to the image sensor. Between the imagesensor and the imaging lens (e.g., between an imaging relay and imaginglens) is an intermediate image plane, at which an optical diffuser isplaced. In this way, the conventional remote requirement of the opticaldiffuser is brought within an image capture system by treating theintermediate image plane as a new ambient object scene. The opticaldiffuser is switchable between a state to cause diffusion to lighttransmitted through the diffuser and a state that does not causediffusion to the light transmitted through the diffuser.

Since the diffuser plane may be fixed relative to main lens, and a loweracceptance lens may be used for the imaging relay, such system is not asimpacted by non-telecentric character in proximity to the intermediateimage plane, as long as the chief cone NAs of both imaging lens andimaging relay have overlap, such that the smaller acceptance cones ofthe imaging relay are substantially filled for all field locationswithin active sensor area, and the diffuser angular exit numericalaperture is strong enough to re-scatter light from substantially allcontent at diffuser plane, blurred or focused, into the acceptance ofthe imaging relay. The imaging relay may include a typical multiple lenselement imaging relay, or a microlens array based imaging relay whichmay serve to reduce system length, and may be composed of multiplelayers of microlens array layers in order to provide erect 1-to-1 relayimaging.

A depth sensing module receives images captured by the image sensor andsenses relative depth of objects in the object scene that is relayed viadiffusion. For example, the amount of blurring caused by the opticaldiffuser to the objects is proportional to a distance of the object fromthe optical diffuser that is disposed internally within the imagecapture system. In this way increased accuracy of depth from diffusiontechniques may be leveraged in common usage scenarios by avoiding aconventional requirement of placing the optical diffuser in the objectspace along with the objects, i.e., outside the camera. Additionally,these techniques may be performed with off the shelf imaging lens,imaging relay and image sensors and thus forgo conventional requirementsof expensive dedicated hardware, thus saving cost to a device thatemploys these techniques. Other examples are also contemplated, furtherdiscussion of which is included in the following sections and shown incorresponding figures.

Another advantage of diffusion techniques over conventional defocus isthat a large aperture lens is not required to achieve the sameresolution. That said, for the case of relayed depth from diffusion,this advantage appears to be primarily in the imaging relay, as the mainimaging lens has enough aperture to create a different sized footprintof the defocused content representing various object z conjugatedistances. By having a differential combination of moderate F/#, such asF/2.5, for imaging lens, and a high (lower cost) F/# for imaging relay,such as F/4 or higher, the image sensor may see a larger depth of focusfor both states, which is advantageous for the non-diffuser state inorder to have larger depth of field, thus greater depth of objects infocus over full range, while main imaging lens has lower F/# in order toincrease cone numerical aperture in order to enable distinction in blursize versus object z conjugate distance. Accordingly, a high enough conenumerical aperture from main imaging lens may be used to form footprintdefocus variation or distinct blur among various image conjugatecontent, while using a lower cone numerical aperture for imaging relay,in order to ensure larger depth of focus at sensor, or larger depth offield for the image space content in proximity to intermediate imageplane.

Thus, although the following discussion describes use of an intermediateimage plane and diffusion for depth sensing, these techniques areapplicable to a wide range of other uses. For example, an intermediateimage plane may be used to reduce depth of field for low NA, high DOFimaging, e.g., to mimic an effect of a high NA imaging system. Inanother example, because an optical diffuser scatters light raystransmitted through the diffuser, the diffuser may be used to increasean effective aperture of an optical system, e.g., a relay lens for animage sensor. This example may thus enable lower-aperture lens systemsto be used in mobile communication devices (e.g., mobile phones),thereby conserving cost and increasing utility of the device by reducingan aperture of a lens of a camera used to capture the images.

In the following discussion, an example environment is first describedthat may employ the techniques described herein. Example procedures arethen described which may be performed in the example environment as wellas other environments. Consequently, performance of the exampleprocedures is not limited to the example environment and the exampleenvironment is not limited to performance of the example procedures.

Example Environment

FIG. 1 is an illustration of an environment 100 in an exampleimplementation that is operable to employ the relayed depth fromdiffusion techniques described herein. The illustrated environment 100includes a computing device 102, which may be configured in a variety ofways.

For example, a computing device may be configured as a dedicated imagecapture device (e.g., a camera), a computer that is capable ofcommunicating over a network, such as a desktop computer, a mobilestation, an entertainment appliance, a set-top box communicativelycoupled to a display device, a wireless phone, a game console, and soforth. Thus, the computing device 102 may range from full resourcedevices with substantial memory and processor resources (e.g., personalcomputers, game consoles) to a low-resource device with limited memoryand/or processing resources (e.g., traditional set-top boxes, hand-heldgame consoles). Additionally, although a single computing device 102 isshown, the computing device 102 may be representative of a plurality ofdifferent devices, such as multiple servers utilized by a business toperform operations such as by a web service, a remote control andset-top box combination, an image capture device and a game consoleconfigured to capture gestures that do not involve touch, and so on.

The computing device 102 is illustrated as including a variety ofhardware components, examples of which include a processing system 104,an example of a computer-readable storage medium illustrated as memory106, a display device 108, and so on. The processing system 104 isrepresentative of functionality to perform operations through executionof instructions stored in the memory 106. Although illustratedseparately, functionality of these components may be further divided,combined (e.g., on an application specific integrated circuit), and soforth.

The computing device 102 is further illustrated as including anoperating system 110. The operating system 110 is configured to abstractunderlying functionality of the computing device 102 to applications 112that are executable on the computing device 102. For example, theoperating system 110 may abstract processing system 104, memory 106,network, and/or display device 108 functionality of the computing device102 such that the applications 112 may be written without knowing “how”this underlying functionality is implemented. The application 112, forinstance, may provide data to the operating system 110 to be renderedand displayed by the display device 108 or printer without understandinghow this rendering will be performed. The operating system 110 may alsorepresent a variety of other functionality, such as to manage a filesystem and user interface that is navigable by a user of the computingdevice 102.

The computing device 102 is also illustrated as including an imagecapture system 114 and a depth sensing module 116. The image capturesystem 114 is representative of functionality to capture images of anobject scene 118, examples of which are illustrated as a dog and treesas objects in the object scene 118. The image capture system 114 maythus include a lens system and image sensor (e.g., a charge coupleddevice), an example of which is shown in greater detail in FIG. 2. Inone or more implementations, the image capture system 114 may alsoinclude specialized depth sensing hardware, such as to support astructured-light depth detection technique through use of astructured-light projector as further described below and thus mayutilize light that is visible or not visible to the human eye.

The depth sensing module 116 is representative of functionality to senseremote depth of objects in the object scene 118 using diffusion. Forexample, the image capture system 114 includes an optical diffuser 120that is configured to introduce an amount of diffusion (e.g., scatter)to light transmitted internally to the image capture system 114, whichis captured as part of the images taken by the image capture system 114.The amount of diffusion introduced to individual objects in the objectscene captured as part of the image is proportional to a distancebetween the objects and the optical diffuser. In this way, the depthsensing module 116 is able to perform depth sensing via relayed depth bythe amount of diffusion of the objects internally to the image capturesystem 114, and thus also internally within a housing 122 of thecomputing device 102 as a whole. In this way, the depth by diffusiontechniques described herein may be employed while avoiding use ofexternal diffusers within the object scene 118 as is required inconventional techniques. Further discussion of the image capture system114 and optical diffuser 120 is described in the following system andshown in a corresponding figure.

FIG. 2 depicts a system 200 in an example implementation showing theimage capture system 114 of FIG. 1 in greater detail as capturing animage of the object scene 118. The image capture system 114 in thisinstance captures light from the object space 118, a path of which isillustrated using lines in the figure. The light is transmitted throughone or more imaging lenses 202 forming a principal plane 204, thenthrough an input polarizer 206 and switchable polarization 208 andtelecentric correction 210 to form an intermediate image plane 212. Theoptical diffuser 120 is disposed proximal to the intermediate imageplane 212. Light then passes through an imaging relay 214 to an imagesensor 216 for processing by a depth sensing module 116. The imagesensor 216 thus captures images that are communicated to the depthsensing module 116 for a variety of uses, such as traditional imagecapture (e.g., photos or videos), depth sensing, and so forth. Note thatboth input polarizer 206 and switchable polarization 208, such as anelectrically switchable polarization rotator, may be placed in alternatelocations along the optical system path, such as (1) before main imaginglens or (2) after telecentric correction 210, as long as input lighttransmits through input polarizer 206 prior to switchable polarization208 and such polarized transmitted light transmits through switchablepolarization 208 prior to intermediate image plane for best results.

The image capture system 114, for instance, leverages diffusion added totransmitted light at the intermediate image plane 212 for depth sensingvia relayed depth from diffusion, e.g., by generating athree-dimensional “Z” map of the object scene 114. The intermediateimage plane 212 is formed at least in part by a lens that performstelecentric correction 210, e.g., to perform lens acceptance matching ofthe imaging lens 202. In this way, the image capture system supportssupport formation of an intermediate image plane 212 within the opticaldiffuser disposed proximally thereto that acts as a filter plane withinthe image capture system 114 with an optical diffuser 120 included nearthe intermediate image plane 212. This supports depth sensing usingvisible light, monochrome or color sensors.

The optical diffuser 120, which may include a variety of diffusionoutput profiles, may diffuse one state of input light polarization,while an orthogonal input light polarization state is allowed totransmit undiffused. In order to limit the impact of motion blur, imagesof both states may be captured in an alternating manner by fasttime-sequential imaging.

The optical diffuser 120 is configurable in a variety of ways tointroduce diffusion to the transmitted light. This may include use ofmechanical (e.g., rotation) or electrical switches to enable polarizedinput light to transmit either diffuse or non-diffuse states through apolarization-dependent diffuser onto the image sensor 216 using therelay lens 210. In an electrical example, a fast polarization rotator,such as a ferroelectric liquid crystal cell or alternative liquidcrystal-based switcher, in conjunction with polarized input light may beused such that alternate frames include alternating diffuse andnon-diffuse states. Input light may be polarized by a typical filmpolarizer, such as Polaroid film, or a wire grid polarizer, the latterbeing useful for broadband applications or narrowband applications usingnear infrared (NIR) light. The optical diffuser 120, for instance, maybe configured to have a random surface relief, alternating opticalangular spreaders, an axicon array, prismatic array, diffractiongrating, micro lens array, both one and two-dimensional versions ofeach, and so on. Further, both states may be captured simultaneously bymaking use of a patterned polarizer aligned and registered over thesensor array cells, such that alternating, interstitially spaced, pixelsdetect orthogonal polarization states. Additional examples of opticaldiffuser configurations are described in relation to FIGS. 3-6 in thefollowing discussion.

Structured light may be added to improve detection of some difficultsituations, such as flat walls. Further, combination and/or sequentialcapturing of content with and without structured light may enable colorcontent as well as improved depth resolve. To further improve signal tonoise, and filter out ambient object space light having wavelengthswhich are outside the band of the illumination light source, a bandpassfilter may be utilized to limit input light that transmits to the imagesensor to be within a range of wavelengths substantially overlappingwith the illumination range of wavelengths, which may be laser sourcebased, such as a speckle pattern or dot pattern, or light projection.

Additionally, since the relayed image is utilized, object distance andimage distance follow a nonlinear relationship based on optical imagingconjugate distances. This aspect provides a realistic representation ofwhat is perceived by the human eye, since depth resolution inherentlyincreases for close objects and reduces for objects at a far distance.This enables capture of a larger content range compared with linearsystems, which may be more efficient for some scenarios involvinglong-range perspective. Linear systems are also contemplated withoutdeparting from the spirit and scope thereof.

FIG. 3 depicts an example implementation 300 of the optical diffuser 120of FIG. 2 that is configured to mechanically switch between polarizedand non-polarized states. This example implementation 300 includes sideand front views 302, 304 of an optical diffuser 306. The opticaldiffuser 306 in this example is configured to rotate such that lighttransmitted through the image capture system 114 is transmitted throughdifferent portions 308, 310, 312, 314 of the optical diffuser 306 atdifferent points in time. The portions 308-314, for instance, mayalternate between functionality to diffuse light and not diffuse light,may include different amounts of diffusion, have diffusion layersembedded at different z placements within laminated stack for eachportion, and so on. The rotation of the optical diffuser 306 in thisinstance is thus synchronized with images captured by the image sensor216 in order to perform depth sensing.

The optical diffuser 306 as shown in the side view 302 includes firstand second substrates 316, 318 having a material 320 disposed betweenthat is configured to provide the diffusion as desired. The materialdisposed between may be volume scattering media in mismatched index, orinclude one or two relief surfaces on one or both of the inner-facingfaces of the two laminated substrates, being laminated by adhesivehaving refractive index which differs from refractive index of thesurface relief surface or surfaces. Thus, diffusion performed by thematerial of the optical diffuser 306 may be passive in this instance dueto the mechanical rotation of the optical diffuser 306 although activeinstances are also contemplated, such as an electrically switchableliquid-crystal cell. Other electrically switchable examples are alsocontemplated in which the optical diffuser does not move and switchingis performed between diffuse and non-diffuse states, such that thesystem has no moving parts, an example of which is described in thefollowing and shown in a corresponding figure.

FIG. 4 depicts an example implementation 400 of the optical diffuser 120of FIG. 2 that is configured to electrically switch between polarizedand non-polarized states. The optical diffuser 402 in this example is apolarization-dependent diffuser formed by embedding a liquid-crystallayer 404 between two substrates 406, 408, with at least one of thesubstrates 406, 408 having a surface relief topography on the innerlayer adjacent to the liquid-crystal layer 404. Thus, the opticaldiffuser 404 is switchable electrically by the depth sensing module 116between polarized and non-polarized states to diffuse or not diffuselight transmitted there through.

FIG. 5 depicts a system 500 in an example implementation of apolarization-sensitive microlens array and polarization-sensitivediffuser. The system 500 includes a liquid-crystal alignment substrate502 and a diffuser substrate 504. Disposed between the substrates isliquid crystal 506 and a microlens array 508 or diffuser surface relief.The liquid-crystal alignment substrate 502 includes a fine linear groovestructure 510 for alignment of liquid crystal orientation, e.g., arubbed surface, grating (i.e., surface having a 1 μm pitch opticalgrating), molded substrate, replicated-on substrate, and so on. Examplesof use of the system include a first example 512 in which inputpolarization is aligned to a non-diffuse state and a second example 514I which input polarization is aligned to a diffuse state.

To null or minimize diffusion & scatter (for non-diffuse state) due todiffusing surface features, a surface relief media refractive index ismatched to liquid crystal ordinary index, n_(o). Since long axis ofliquid crystal inherently aligns to groove features of alignmentsubstrate, the extraordinary index axis aligns along the grooves. Thus,when input polarized light is oriented in no axis the diffuser does notscatter light. For orthogonal polarized input light, having polarizationoriented in n_(e) axis, light is scattered by the diffuse characterdefined by both a profile of surface relief and index differentialbetween the extraordinary refractive index n_(e) and surface reliefmedia refractive index, set to match n_(o).

Various surface relief profiles may be used to achieve a rescatteringeffect at the diffuser plane, such as a Gaussian diffuser, based onrandom surface relief (or limited-random, pseudo-random), a microlensarray (MLA), axicon array (array of cones), and may be one-dimensionalor two-dimensional in angular spread character. While a physical wheelor moving plate, having diffuse and non-diffuse regions, may be used toachieve the diffuse and non-diffuse states, use of a polarizer topolarize the input light along with an electrically-switchable liquidcrystal polarization rotator to switch between orthogonal polarizationstates may enable solid state active time-sequential system having nomoving parts.

FIG. 6a depicts a system 600 in an example implementation showing afirst polarization switching option. In this example, randompolarization S&P light 602 is filtered by a linear polarizer 604 thatresults in linearly polarized light 606. The linearly polarized light606 is then transmitted through an electrically switchableliquid-crystal polarization rotator 608 and a polarization-sensitivediffuser 610 for capture by a 2× speed image sensor 612 to capturealternating diffused and non-diffused images for processing by the depthsensing module 116.

FIG. 6b depicts a system 650 in an example implementation showing apolarization option that supports simultaneous capture of a plurality ofpolarization states. In this example, random polarization S&P light 652is also transmitted through a polarization-sensitive diffuser 654. Theimage sensor 656 is configured to support simultaneous capture of bothdiffuse and non-diffuse states using alternation portions, e.g., as apatterned wire grid polarizer array aligned and registered with, andjust over or before, the pixels of the image sensor to avoid motionartifacts. Although not shown, both layouts includes a main lens andoptical relay with polarization-dependent diffuser placed nearintermediate image plane formed by the main lens as described inrelation to FIG. 2.

As described above, in a conventional diffusion setup an opticaldiffuser is placed between the objects in a scene and a camera, and ablurred image is captured with the diffuser, while a non-blurred imagedis captured without the diffuser. For a given diffuser strength having agiven or known angular exit profile, the amount of the blur of objectsin scene image depends on the z separation distance between the diffuserand objects in scene. This implies that an image of the field of view iscomposed of a number of different sized blurs each representing adifferent angle within the field of view. In other words, the diffusedimage includes the non-diffused scene image convolved with differentdiffuser blur sizes corresponding to each pixel location within a fieldof view of the image.

The size of the diffuse blur corresponding to each pixel is determinedin order to deduce the depth information, which may include use of anumber of algorithms to estimate and map a diffuse blur size map. Thisis then translated into a z map due to knowledge of the diffuser exitangle profile angular size and intensity shape. Such a system, though,is limited in usage as the diffuser must be placed in the scene in frontof but near objects in scene, so the system is not self-contained.

In order to enable such a strategy to provide a z map for the case ofrelayed depth from diffuser, which is self-contained as shown in FIG. 2,the image of scene imaged through the imaging lens 202 is treated as thenew object scene from which both diffuse and non-diffuse images arecaptured by applying an appropriate fine-featured diffuser near theintermediate image plane 212. Since the conjugate z distances at theimage, or new object scene, are related approximately by a thin lensequation, there is now a nonlinear mapping between the resulting imagespace z map inferred from diffuse blur size map, and the actual final zmap, thereby representing the real object scene 118.

The final depth (i.e., “z”) map is then calculated by applying this lensequation relationship, which describes the mapping of real object zdistances to imaged conjugate z distances after being imaged through theimaging lens 202, thus translating an image space z map into a final zmap. Alternatively, the amount of blur of objects in scene betweenstates may be assessed and calibrated against known object distances inorder to close the loop on object z mapping.

Note that since the imaged object scene becomes the object scene inputto depth from diffusion, the optical diffuser 120 location may be placedat any z distance relative to the imaged object scene. In some cases,diffuse and non-diffuse images may be captured for optical diffusersplaced at multiple diffuser planes, which may improve resolve and/orsensing depth capability. Since the imaged object scene images objectsat infinity distance at lens focal length, and closer object distancesare dictated by the imaging conjugates (e.g., on order with a thin lensequation), the image space z map resolution increments become nonlinearwith z distance from lens. This effect can be useful in scenarios wherehigh dynamic range in z is desirable, and higher resolve is desiredcloser to image capture system 114. One such scenario is designed tomimic human eye response or z resolve expectations based on perspectivedistance, where more resolve is desired close to an eye, andprogressively less resolve increment in z for far distances, due todepth of field.

FIGS. 7 and 8 depict graphs 700, 800 illustrating examples of nonlinearmapping to the z distance deduced by the depth from diffusion techniqueswhich follows optical image conjugates of the image capture system 114.For the graph 700 of FIG. 7, an imaging lens 202 having focal length ofsix millimeters is used along with an embedded diffuse strengthapproaching 10° FWHM. The linear incremented z distances at or near theintermediate image plane then correspond to image conjugate distances inthe object space portraying the relationship close to an imaging lensrelationship. For f=6 mm, the images captured object content from 100millimeters away to as much as five to six meters away from the imagecapture system 114. Thus, FIG. 7 illustrates the relationship betweenlinear incremented z distance at intermediate image plane and the realobject space for various imaging lens focal lengths.

A change of focal length of the imaging lens 202 can enable not onlydifferent field of view for the system, but also a change in thenonlinear distance mapping as shown in FIG. 8. FIG. 8 depicts an imagedefocus range versus object conjugate distance for various imaging lensfocal lengths. This nonlinear mapping may be useful for scenarios whereit is desirable to mimic human eye perspective in terms of distanceresolve vs z distance as described above.

FIG. 9 depicts an example graph 900 of spotsize blur for various objectdistances for a diffuser placed at image space conjugate for far objectdistance. FIG. 10 depicts an example graph 1000 of spotsize blur forvarious object distances for a diffuser placed at image space conjugatefor near object distance. When performing a depth from diffusion using adiffuser in the object scene, depth is assessed only for objects whichare placed behind the diffuser. However, by imaging the object sceneinto image space within proximity of an intermediate image plane,multiple diffuser placement options are now possible. Scenarios include(1) placement of diffuser at image space conjugate, or focus, of theobject distance representing the far limit of depth sensing range asshown in the graph 900 of FIG. 9, and (2) placement of diffuser at imagespace conjugate, or focus, of the object distance representing the nearlimit of depth sensing range as shown in the graph 1000 of FIG. 10.

For the diffuse state, when the optical diffuser 120 is placed at farobject image conjugate, relayed image of the diffuser plane shows farobject in focus and near objects blurred, whereas when diffuser isplaced at the near object image conjugate, relayed image of diffuserplane shows near objects in focus and far objects blurred. Placement ofthe diffuser in the middle of a desired target range allows blur to havesome localized symmetry in positive and negative z directions, thuspossible ambiguity and would typically not be desirable, unless theintent is to enable active positioning of an object, perhaps throughfeedback from the system. While blur symmetry may be utilized, it isexpected that useful scenarios include matching best focus for eithertarget z end limits, such as Far or Near, to avoid localized inversioneffects due to such focus crossover.

Since the diffuser serves as a plane of scatter centers, or rescatteringplane, the footprints of spotsize at the diffuser dictate the relativesize of blur in relayed image, and since image conjugate z distance isdependent on object conjugate distance, blur becomes a function ofobject z distance. Best focus is determined by placement of the diffuserplane within image space, such that best focus and extreme blur endlimits are strategically determined by diffuser placement plane, whichis then relayed into image at sensor plane.

Strength of the diffuser is important to the extent that diffuser exitangle, or exit numerical aperture, or exit angular profile, are to belarge enough to rescatter a portion of image footprints at diffuserplane into the relay lens acceptance to ensure that the blur size isseen at image sensor plane. Matching diffuser exit numerical aperture tomain imaging lens numerical aperture may ensure blur size is maintained,whereas too low diffuser exit numerical aperture provides fractionalblur amount, or factor, and wastes usage of lens numerical aperture.Reasonable results have been obtained with lens numerical aperture inthe F/2 to F/4 range, but other numerical apertures are possible. On theother extreme, if the diffuser exit numerical aperture is substantiallylarger than imaging lens numerical aperture, then much light may bescattered beyond the acceptance numerical aperture of the relay lens, orrelay acceptance, and thus reduce efficiency of the system. For thesereasons, for optimal blur effect and high efficiency, choice of diffusernumerical aperture may be based on, and on order of the acceptance ofboth main imaging lens and relay lens. Light loss for case of using toohigh exit numerical aperture for diffuse state may be mitigated bycompensation of the grey level in image, but it is efficient to ensurecapture of all or most of the scattered light through appropriate choiceof relay acceptance, and limited or controlled profile of diffuserand/or MLA.

FIG. 11 depicts an example implementation of time-sequential depth fromdiffusion using a polarization-sensitive microlens array. A firstexample 1102 shows polarization aligned with a non-diffuse state and asecond example 1104 shows polarization aligned with a diffuse state. Inthis example, diffuse state matches best focus at near field, i.e., theoptical diffuser 120 is placed for best focus at near object imageconjugate, as far objects 1106 (e.g., the sign) have blur but nearobjects 1108 do not, e.g., the park sign.

Example Procedures

The following discussion describes remote depth sensing via relayeddepth from diffusion techniques that may be implemented utilizing thepreviously described systems and devices. Aspects of each of theprocedures may be implemented in hardware, firmware, software, or acombination thereof. The procedures are shown as a set of blocks thatspecify operations performed by one or more devices and are notnecessarily limited to the orders shown for performing the operations bythe respective blocks. In portions of the following discussion,reference will be made to the figures described above.

Functionality, features, and concepts described in relation to theexamples of FIGS. 1-11 may be employed in the context of the proceduresdescribed herein. Further, functionality, features, and conceptsdescribed in relation to different procedures below may be interchangedamong the different procedures and are not limited to implementation inthe context of an individual procedure. Moreover, blocks associated withdifferent representative procedures and corresponding figures herein maybe applied together and/or combined in different ways. Thus, individualfunctionality, features, and concepts described in relation to differentexample environments, devices, components, and procedures herein may beused in any suitable combinations and are not limited to the particularcombinations represented by the enumerated examples.

FIG. 12 depicts a procedure 1200 in an example implementation in which atechnique is described to perform remote depth sensing of objects in animage scene using diffusion by a computing device. One or more imagesare received by the computing device of an image scene from an imagecapture system having diffusion applied internally by the image capturesystem (block 1202). The computing device 102, for instance, may includean image capture system 114 that captures an image of the object scene118. The image capture system 114 includes an optical diffuser 120 thatis disposed proximal to an intermediate image plane 212 that is internalto the system.

A distance to one or more objects in the image scene is determined bythe computing device based on an amount of blurring exhibited by the oneor more objects in the received images (block 1204). The depth, forinstance, may be determined by the depth sensing module 116 to beproportional, but not linear, to the amount of blurring exhibitedthrough a comparison of blurred and non-blurred versions of the images.This is then used to compute a depth map of the object scene 118. Thedetermined distance is output by the computing device (block 1206), suchas through part of the depth map. This may be used to support a varietyof functionality, such as a natural user interface, object recognition,three-dimensional mapping, and so on.

Example System and Device

FIG. 13 illustrates an example system generally at 1300 that includes anexample computing device 1302 that is representative of one or morecomputing systems and/or devices that may implement the varioustechniques described herein. This is illustrated through inclusion ofthe depth sensing module 116, and may also include the image capturesystem 114 and internal optical diffuser 120 of FIG. 1. The computingdevice 1302 may be, for example, a server of a service provider, adevice associated with a client (e.g., a client device), an on-chipsystem, and/or any other suitable computing device or computing system.

The example computing device 1302 as illustrated includes a processingsystem 1304, one or more computer-readable media 1306, and one or moreI/O interface 1308 that are communicatively coupled, one to another.Although not shown, the computing device 1302 may further include asystem bus or other data and command transfer system that couples thevarious components, one to another. A system bus can include any one orcombination of different bus structures, such as a memory bus or memorycontroller, a peripheral bus, a universal serial bus, and/or a processoror local bus that utilizes any of a variety of bus architectures. Avariety of other examples are also contemplated, such as control anddata lines.

The processing system 1304 is representative of functionality to performone or more operations using hardware. Accordingly, the processingsystem 1304 is illustrated as including hardware element 1313 that maybe configured as processors, functional blocks, and so forth. This mayinclude implementation in hardware as an application specific integratedcircuit or other logic device formed using one or more semiconductors.The hardware elements 1313 are not limited by the materials from whichthey are formed or the processing mechanisms employed therein. Forexample, processors may be comprised of semiconductor(s) and/ortransistors (e.g., electronic integrated circuits (ICs)). In such acontext, processor-executable instructions may beelectronically-executable instructions.

The computer-readable storage media 1306 is illustrated as includingmemory/storage 1312. The memory/storage 1312 represents memory/storagecapacity associated with one or more computer-readable media. Thememory/storage component 1312 may include volatile media (such as randomaccess memory (RAM)) and/or nonvolatile media (such as read only memory(ROM), Flash memory, optical disks, magnetic disks, and so forth). Thememory/storage component 1312 may include fixed media (e.g., RAM, ROM, afixed hard drive, and so on) as well as removable media (e.g., Flashmemory, a removable hard drive, an optical disc, and so forth). Thecomputer-readable media 1306 may be configured in a variety of otherways as further described below.

Input/output interface(s) 1308 are representative of functionality toallow a user to enter commands and information to computing device 1302,and also allow information to be presented to the user and/or othercomponents or devices using various input/output devices. Examples ofinput devices include a keyboard, a cursor control device (e.g., amouse), a microphone, a scanner, touch functionality (e.g., capacitiveor other sensors that are configured to detect physical touch), a camera(e.g., which may employ visible or non-visible wavelengths such asinfrared frequencies to recognize movement as gestures that do notinvolve touch), and so forth. Examples of output devices include adisplay device (e.g., a monitor or projector), speakers, a printer, anetwork card, tactile-response device, and so forth. Thus, the computingdevice 1302 may be configured in a variety of ways as further describedbelow to support user interaction.

Various techniques may be described herein in the general context ofsoftware, hardware elements, or program modules. Generally, such modulesinclude routines, programs, objects, elements, components, datastructures, and so forth that perform particular tasks or implementparticular abstract data types. The terms “module,” “functionality,” and“component” as used herein generally represent software, firmware,hardware, or a combination thereof. The features of the techniquesdescribed herein are platform-independent, meaning that the techniquesmay be implemented on a variety of commercial computing platforms havinga variety of processors.

An implementation of the described modules and techniques may be storedon or transmitted across some form of computer-readable media. Thecomputer-readable media may include a variety of media that may beaccessed by the computing device 1302. By way of example, and notlimitation, computer-readable media may include “computer-readablestorage media” and “computer-readable signal media.”

“Computer-readable storage media” may refer to media and/or devices thatenable persistent and/or non-transitory storage of information incontrast to mere signal transmission, carrier waves, or signals per se.Thus, computer-readable storage media refers to non-signal bearingmedia. The computer-readable storage media includes hardware such asvolatile and non-volatile, removable and non-removable media and/orstorage devices implemented in a method or technology suitable forstorage of information such as computer readable instructions, datastructures, program modules, logic elements/circuits, or other data.Examples of computer-readable storage media may include, but are notlimited to, RAM, ROM, EEPROM, flash memory or other memory technology,CD-ROM, digital versatile disks (DVD) or other optical storage, harddisks, magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, or other storage device, tangible media, orarticle of manufacture suitable to store the desired information andwhich may be accessed by a computer.

“Computer-readable signal media” may refer to a signal-bearing mediumthat is configured to transmit instructions to the hardware of thecomputing device 1302, such as via a network. Signal media typically mayembody computer readable instructions, data structures, program modules,or other data in a modulated data signal, such as carrier waves, datasignals, or other transport mechanism. Signal media also include anyinformation delivery media. The term “modulated data signal” means asignal that has one or more of its characteristics set or changed insuch a manner as to encode information in the signal. By way of example,and not limitation, communication media include wired media such as awired network or direct-wired connection, and wireless media such asacoustic, RF, infrared, and other wireless media.

As previously described, hardware elements 1313 and computer-readablemedia 1306 are representative of modules, programmable device logicand/or fixed device logic implemented in a hardware form that may beemployed in some embodiments to implement at least some aspects of thetechniques described herein, such as to perform one or moreinstructions. Hardware may include components of an integrated circuitor on-chip system, an application-specific integrated circuit (ASIC), afield-programmable gate array (FPGA), a complex programmable logicdevice (CPLD), and other implementations in silicon or other hardware.In this context, hardware may operate as a processing device thatperforms program tasks defined by instructions and/or logic embodied bythe hardware as well as a hardware utilized to store instructions forexecution, e.g., the computer-readable storage media describedpreviously.

Combinations of the foregoing may also be employed to implement varioustechniques described herein. Accordingly, software, hardware, orexecutable modules may be implemented as one or more instructions and/orlogic embodied on some form of computer-readable storage media and/or byone or more hardware elements 1313. The computing device 1302 may beconfigured to implement particular instructions and/or functionscorresponding to the software and/or hardware modules. Accordingly,implementation of a module that is executable by the computing device1302 as software may be achieved at least partially in hardware, e.g.,through use of computer-readable storage media and/or hardware elements1313 of the processing system 1304. The instructions and/or functionsmay be executable/operable by one or more articles of manufacture (forexample, one or more computing devices 1302 and/or processing systems1304) to implement techniques, modules, and examples described herein.

As further illustrated in FIG. 13, the example system 1300 enablesubiquitous environments for a seamless user experience when runningapplications on a personal computer (PC), a television device, and/or amobile device. Services and applications run substantially similar inall three environments for a common user experience when transitioningfrom one device to the next while utilizing an application, playing avideo game, watching a video, and so on.

In the example system 1300, multiple devices are interconnected througha central computing device. The central computing device may be local tothe multiple devices or may be located remotely from the multipledevices. In one embodiment, the central computing device may be a cloudof one or more server computers that are connected to the multipledevices through a network, the Internet, or other data communicationlink.

In one embodiment, this interconnection architecture enablesfunctionality to be delivered across multiple devices to provide acommon and seamless experience to a user of the multiple devices. Eachof the multiple devices may have different physical requirements andcapabilities, and the central computing device uses a platform to enablethe delivery of an experience to the device that is both tailored to thedevice and yet common to all devices. In one embodiment, a class oftarget devices is created and experiences are tailored to the genericclass of devices. A class of devices may be defined by physicalfeatures, types of usage, or other common characteristics of thedevices.

In various implementations, the computing device 1302 may assume avariety of different configurations, such as for computer 1314, mobile1316, and television 1318 uses. Each of these configurations includesdevices that may have generally different constructs and capabilities,and thus the computing device 1302 may be configured according to one ormore of the different device classes. For instance, the computing device1302 may be implemented as the computer 1314 class of a device thatincludes a personal computer, desktop computer, a multi-screen computer,laptop computer, netbook, and so on.

The computing device 1302 may also be implemented as the mobile 1316class of device that includes mobile devices, such as a mobile phone,wearables (e.g., wrist bands, pendants, rings, etc.) portable musicplayer, portable gaming device, a tablet computer, a multi-screencomputer, and so on. The computing device 1302 may also be implementedas the television 1318 class of device that includes devices having orconnected to generally larger screens in casual viewing environments.These devices include televisions, set-top boxes, gaming consoles, andso on. Other devices are also contemplated, such as appliances,thermostats and so on as part of the “Internet of Things.”

The techniques described herein may be supported by these variousconfigurations of the computing device 1302 and are not limited to thespecific examples of the techniques described herein. This functionalitymay also be implemented all or in part through use of a distributedsystem, such as over a “cloud” 1320 via a platform 1322 as describedbelow.

The cloud 1320 includes and/or is representative of a platform 1322 forresources 1324. The platform 1322 abstracts underlying functionality ofhardware (e.g., servers) and software resources of the cloud 1320. Theresources 1324 may include applications and/or data that can be utilizedwhile computer processing is executed on servers that are remote fromthe computing device 1302. Resources 1324 can also include servicesprovided over the Internet and/or through a subscriber network, such asa cellular or Wi-Fi network.

The platform 1322 may abstract resources and functions to connect thecomputing device 1302 with other computing devices. The platform 1322may also serve to abstract scaling of resources to provide acorresponding level of scale to encountered demand for the resources1324 that are implemented via the platform 1322. Accordingly, in aninterconnected device embodiment, implementation of functionalitydescribed herein may be distributed throughout the system 1300. Forexample, the functionality may be implemented in part on the computingdevice 1302 as well as via the platform 1322 that abstracts thefunctionality of the cloud 1320.

CONCLUSION AND EXAMPLE IMPLEMENTATIONS

Example implementations described herein include, but are not limitedto, one or any combinations of one or more of the following examples:

Remote depth sensing techniques are described via relayed depth fromdiffusion. In one or more examples, a remote depth sensing system isconfigured to sense depth as relayed from diffusion. The system includesan image capture system including an image sensor and an imaging lensconfigured to transmit light to the image sensor through an intermediateimage plane that is disposed between the imaging lens and the imagesensor, the intermediate plane having an optical diffuser disposedproximal thereto that is configured to diffuse the transmitted light.The system also includes a depth sensing module configured to receiveone or more images from the image sensor and determine a distance to oneor more objects in an object scene captured by the one or more imagesusing a depth by diffusion technique that is based at least in part onan amount of blurring exhibited by respective said objects in the one ormore images.

An example as described alone or in combination with any of the above orbelow examples, wherein the optical diffuser is configured tomechanically switch polarization states to diffuse the transmittedlight.

An example as described alone or in combination with any of the above orbelow examples, wherein the optical diffuser is configured toelectrically switch polarization states to diffuse the transmittedlight.

An example as described alone or in combination with any of the above orbelow examples, wherein the image capture system includes a linearpolarizer and the optical diffuser is a polarization-sensitive diffuser.

An example as described alone or in combination with any of the above orbelow examples, wherein the polarization-sensitive diffuser includes alaminate structure having an embedded surface relief laminated with anadjacent liquid crystal layer that is aligned to provide diffusion in apolarization state and does not provide the diffusion for an orthogonalpolarization state.

An example as described alone or in combination with any of the above orbelow examples, wherein an optical path difference (OPD) is minimized bythe laminate structure between the polarization state and the orthogonalpolarization state.

An example as described alone or in combination with any of the above orbelow examples, wherein the image sensor is configured to capture aplurality of polarization states simultaneously from the opticaldiffuser.

An example as described alone or in combination with any of the above orbelow examples, wherein the optical diffuser is configured to have arandom surface relief, alternating optical angular spreaders, an axiconarray, prismatic array, diffraction grating, or micro lens array.

An example as described alone or in combination with any of the above orbelow examples, wherein the image capture system includes a structuredlight illuminator, an output of which is usable by the depth sensingmodule as captured by the one or more images to determine the distanceto the one or more objects in the object scene.

An example as described alone or in combination with any of the above orbelow examples, wherein the transmitted light is not visible to a humaneye.

In one or more examples, a technique is described to perform remotedepth sensing of objects in an image scene using diffusion by acomputing device. The technique includes receiving one or more images bythe computing device of an image scene from an image capture systemhaving diffusion applied internally by the image capture system,determining a distance to one or more objects in the image scene by thecomputing device based on an amount of blurring exhibited by the one ormore objects in the received images, and outputting the determineddistance by the computing device.

An example as described alone or in combination with any of the above orbelow examples, further comprising controlling the application of thediffusion by the computing device.

An example as described alone or in combination with any of the above orbelow examples, wherein the controlling is performed mechanically toswitch polarization states to diffuse light transmitted internallywithin the image capture system.

An example as described alone or in combination with any of the above orbelow examples, wherein the controlling is performed mechanically toswitch polarization states to diffuse light transmitted internallywithin the image capture system.

In one or more examples, an image capture system includes an imaginglens configured to transmit light from an object scene, an image sensorconfigured to capture the transmitted light from the object scene toform one or more images, and an optical diffuser disposed within anintermediate image plane between the imaging lens and the image sensor,the optical diffuser increasing a depth of field available to the imagesensor from the imaging lens.

An example as described alone or in combination with any of the above orbelow examples, further comprising a depth sensing module configured toreceive one or more images from the image sensor and determine adistance to one or more objects in an object scene captured by the oneor more images a depth by diffusion technique that is based at least inpart on an amount of blurring exhibited by respective said objects inthe one or more images.

An example as described alone or in combination with any of the above orbelow examples, wherein the application of the diffusion by the opticaldiffuser is switchable between diffused and non-diffused states.

An example as described alone or in combination with any of the above orbelow examples, wherein the switching is performed mechanically toswitch polarization states to diffuse light transmitted internallywithin the image capture system.

An example as described alone or in combination with any of the above orbelow examples, wherein the switching is performed electrically toswitch polarization states to diffuse light transmitted internallywithin the image capture system.

An example as described alone or in combination with any of the above orbelow examples, wherein the optical diffuser is configured to have arandom surface relief, alternating optical angular spreaders, an axiconarray, prismatic array, diffraction grating, or micro lens array.

Although the example implementations have been described in languagespecific to structural features and/or methodological acts, it is to beunderstood that the implementations defined in the appended claims isnot necessarily limited to the specific features or acts described.Rather, the specific features and acts are disclosed as example forms ofimplementing the claimed features.

What is claimed is:
 1. A remote depth sensing system configured to sensedepth as relayed from diffusion, the system comprising: an image capturesystem including an image sensor, an imaging lens configured to transmitlight to the image sensor through an intermediate image plane that isdisposed behind the imaging lens within the image capture system, and anoptical diffuser disposed proximal to the intermediate image plane andconfigured to switch between a diffusing state and a non-diffusingstate, where in the diffusing state the optical diffuser is configuredto diffuse the light transmitted to the image sensor and in thenon-diffusing state the optical diffuser is configured to not diffusethe light transmitted to the image sensor, wherein the image capturesystem is configured to 1) alternately switch the optical diffuserbetween the diffusing state and the non-diffusing state for a pluralityof images, 2) while the optical diffuser is in the diffusing state,capture a first set of images of a scene via the image sensor, and 3)while the optical diffuser is in the non-diffusing state, capture asecond set of images of the scene via the image sensor, wherein theplurality of images include alternating diffuse and non-diffuse imagesof the first and second sets; and a depth sensing module configured to(1) receive the first set of images, (2) receive the second set ofimages of the scene from the image sensor, and (3) determine a distanceto one or more objects in the scene captured by the first and secondsets of images using a depth by diffusion technique that is based atleast in part on an amount of blurring exhibited by respective saidobjects in the first and second sets of images.
 2. A system as describedin claim 1, wherein the optical diffuser is configured to mechanicallyswitch polarization states to diffuse the transmitted light.
 3. A systemas described in claim 1, wherein the optical diffuser is configured toelectrically switch polarization states to diffuse the transmittedlight.
 4. A system as described in claim 1, wherein the image capturesystem includes a linear polarizer and the optical diffuser is apolarization-sensitive diffuser.
 5. A system as described in claim 4,wherein the polarization-sensitive diffuser includes a laminatestructure having an embedded surface relief laminated with an adjacentliquid crystal layer that is aligned to provide diffusion in apolarization state and does not provide the diffusion for an orthogonalpolarization state.
 6. A system as described in claim 5, wherein anoptical path difference (OPD) is minimized by the laminate structurebetween the polarization state and the orthogonal polarization state. 7.A system as described in claim 1, wherein the image sensor is configuredto capture a plurality of polarization states simultaneously from theoptical diffuser.
 8. A system as described in claim 1, wherein theoptical diffuser is configured to have a random surface relief,alternating optical angular spreaders, an axicon array, prismatic array,diffraction grating, or micro lens array, such that the optical diffuserprovides an exit numerical aperture in at least one angular dimension.9. A system as described in claim 1, wherein the image capture systemincludes a structured light illuminator, an output of which is usable bythe depth sensing module as captured by the one or more images todetermine the distance to the one or more objects in the scene.
 10. Asystem as described in claim 1, wherein the transmitted light is notvisible to a human eye.
 11. A system as described in claim 1, whereinthe image capture system further includes a telecentric correction lenspositioned intermediate the imaging lens and the image sensor, whereinthe telecentric correction lens is configured to perform lens acceptancematching of the imaging lens to form the intermediate image plane, andwherein the optical diffuser is positioned proximate to the telecentriccorrection lens.
 12. A method of remote depth sensing of objects in ascene using diffusion by an image capture device, the method comprising:alternately switching an optical diffuser positioned between an imaginglens and an image sensor of the image capture device between a diffusingstate and a non-diffusing state for a plurality of images, where in thediffusing state the optical diffuser is configured to diffuse lighttransmitted from the imaging lens to the image sensor; while the opticaldiffuser is in the diffusing state, capturing a first set of images of ascene via the image sensor; while the optical diffuser is in thenon-diffusing state, capturing a second set images of the scene via theimage sensor, wherein the plurality of images include alternatingdiffuse and non-diffuse images of the first and second sets; determininga distance to one or more objects in the scene based on an amount ofblurring exhibited by the one or more objects in the first and secondsets of images; and outputting the determined distance.
 13. A method asdescribed in claim 12, wherein the optical diffuser is mechanicallyswitched between the diffusing state and the non-diffusing state.
 14. Amethod as described in claim 12, wherein the optical diffuser iselectrically switched between the diffusing state and the non-diffusingstate.
 15. An image capture system comprising: an imaging lensconfigured to transmit light from a scene; an image sensor; and anoptical diffuser disposed within an intermediate image plane positionedbetween the imaging lens and the image sensor, wherein the opticaldiffuser configured to switch between a diffusing state and anon-diffusing state, where in the diffusing state the optical diffuseris configured to diffuse the light transmitted to the image sensor toincrease a depth of field available to the image sensor from the imaginglens, and where in the non-diffusing state the optical diffuser isconfigured to not diffuse the light transmitted to the image sensor,wherein the image capture system is configured to 1) alternately switchthe optical diffuser between the diffusing state and the non-diffusingstate for a plurality of images, 2) while the optical diffuser is in thediffusing state, capture a first set of images of the scene via theimage sensor, and 3) while the optical diffuser is in the non-diffusingstate, capture a second set of images of the scene via the image sensor,wherein the plurality of images include alternating diffuse andnon-diffuse images of the first and second sets.
 16. An image capturesystem as described in claim 15, further comprising a depth sensingmodule configured to receive the first and second sets of images fromthe image sensor and determine a distance to one or more objects in thescene captured by the first and second sets of images using a depth bydiffusion technique that is based at least in part on an amount ofblurring exhibited by respective said objects in the first and secondsets of images.
 17. An image capture system as described in claim 15,wherein the optical diffuser is configured to mechanically switchbetween the diffusing state and the non-diffusing state.
 18. An imagecapture system as described in claim 15, wherein the optical diffuser isconfigured to electrically switch between the diffusing state and thenon-diffusing state.
 19. An image capture system as described in claim15, wherein the optical diffuser is configured to have a random surfacerelief, alternating optical angular spreaders, an axicon array,prismatic array, diffraction grating, or micro lens array such that theoptical diffuser provides an exit numerical aperture in at least oneangular dimension.
 20. An image capture system as described in claim 15,wherein the image capture system further includes a telecentriccorrection lens positioned intermediate the imaging lens and the imagesensor, wherein the telecentric correction lens is configured to performlens acceptance matching of the imaging lens to form the intermediateimage plane, and wherein the optical diffuser is positioned proximate tothe telecentric correction lens.